Driver behavior modification techniques aim to increase traffic safety and decrease emissions by encouraging drivers to operate their vehicles more safely, more sustainably. Such techniques include educational initiatives, incentive systems and technological interventions such as eco-driving training or GPS-based eco-routing systems.

Research in naturalistic driving hinges on its ability to establish contextual connections between baseline and event periods, and their epochs of relevance. Findings from automation studies must therefore be compared against strong experimental controls for causality analysis.

Safety

Research on driver behaviour and traffic safety is limited, evidenced by the small number of articles published and their distribution across journals. An analysis of this research indicates that most highly cited articles focus on specific driving behavior characteristics while international articles tend to cover broader topics like country comparisons or accident statistics.

One recent study was able to make use of data from a trucking fleet which had implemented a behavior-based driver feedback system, which allowed researchers to utilize baseline period information before rolling out this feedback system and compare drivers in control and treatment groups.

Natural experiments offer an ideal way to study the impact of vehicle modifications. However, it should be remembered that natural experiments rely on precise contextual matches between baseline and event epochs; any deviation can lead to uncontrolled confounding and invalidate findings.

Fuel Economy

Fuel economy can be measured using various techniques; burned gasoline converts into heat that dissipates through aerodynamic losses and tire friction, before some of it can be recaptured through regenerative braking systems and transformed back into electricity to recharge the battery. Fuel consumption also depends upon driving behavior – frequent acceleration and heavy braking waste energy while cold weather reduces performance since engine must run longer in order to warm up properly.

Gas prices’ constant fluctuations present a challenge to regulations that rely on this price signal to achieve optimal cost-effectiveness, and other factors which contribute to traffic crashes include speeding, recklessness, alcohol and drugs use, poor road design and failure to understand or follow signs. Road Safety Education Victoria [7] notes that drivers may become distracted due to cell phones, music streaming or socialising with friends; all of these elements can be addressed through motivation/education for drivers as well as stricter law enforcement measures.

Emissions

Factors contributing to road traffic accidents include driver behavior. Therefore, research on driver safety is of vital importance; however, data availability may limit what can be studied – therefore a more holistic approach must be taken, with continent-wide and country-specific databases that reflect accident rates being implemented as necessary.

Bibliometric analyses indicate that while research into this topic is on the rise, it remains an emerging field with limited scholarly foundation. This can be seen through low h-indices and keyword co-occurrence. Furthermore, African-focused research remains focused on identification while international works have begun exploring intervention identification and effectiveness analysis.

Recently, researchers used aggregate fleet data to investigate the effect of feedback systems on drivers’ adherence to traffic laws. Their results show that these systems can have significant positive results in terms of reducing emissions and preventing accidents – even without being used actively by drivers themselves.

Technology

To combat driving habits that contribute to careless driving and increased fuel consumption, technologies must be implemented that enable drivers to change their behavior. Such technologies include educational programs, incentives for eco-friendly driving and technological tools like real-time feedback from in-car systems.

Naturalistic research methods offer a key way to examine driver behavior, but they come with several drawbacks. Notably, naturalistic studies do not employ experimental interventions to control study conditions – potentially leading to confounding variables and misinterpretation of findings.

This study used both naturalistic and experimental approaches to understand how drivers respond to vehicle automation. Participants used vehicles equipped with Level 2 partial automation during their work commute for 6-8 weeks of observation and driving; one day was designated each week as experimental control day for statistical evaluation of driver behavior on controlled access highways under both control and automation conditions.